Adversarial examples are the inputs to machine learning models that result in erroneous outputs. which are usually generated from normal inputs via subtle modification and seem to remain unchanged to human observers. They have severely threatened the applications of machine learning. especially in the areas with high-security requirements. https://oznicoes.shop/product-category/k-boots/
Markov Chain Based Efficient Defense Against Adversarial Examples in Computer Vision
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